Comparative analysis of spatial and transform domain methods for meningioma subtype classification

Pattern recognition in histopathological image analysis requires new techniques and methods. Various techniques have been presented and some state of the art techniques have been applied to complex textural data in histological images. In this paper, we compare the novel Adaptive Discriminant Wavelet Packet Transform (ADWPT) with a few prominent techniques in texture analysis namely Local Binary Patterns (LBP), Grey Level Co-occurrence Matrices (GLCMs) and Gabor Transforms. We show that ADWPT is a better technique for Meningioma subtype classification and produces classification accuracies of as high as 90%

Transcriptional Regulation of Non-Coding RNAs by Retinoblastoma Tumor Suppressor Protein

Recent advances in whole transcriptome sequencing have revealed that the majority of the genome is transcribed but only 1% of transcripts are coded for protein biosynthesis. This remaining ‘junk DNA’ includes non-coding RNA species (ncRNA), which have been implicated in modulating tumorigenesis as well as tumor suppression if they are misexpressed. Recent experiments indicate that loss of the Retinoblastoma tumor suppressor protein (pRB), a transcriptional co-regulator, alters the expression of both coding and non-coding transcripts. This project seeks to understand if misexpression of these ncRNAs plays a role in the pleiotropic effects of pRB loss in cancer

Effect of Salvadora persica Linn root aqueous extract on oral epithelial dysplasia and oral cancer cell lines

Purpose: To evaluate the potential chemo-preventive and anti-oral cancer effects of Salvadora persica (S. persica) on oral epithelial dysplasia and oral squamous cell carcinoma cell lines. Methods: Aqueous S. persica root extracts were prepared at concentrations up to 15.75 mg/mL and applied to oral epithelial dysplasia (DOK), oral squamous cell carcinoma (PE/CA-PJ15), and periodontal ligament fibroblast (PDL) cell lines. The effect of the extract on cell survival and proliferation was determined using MTT assay, while its effect on apoptosis in DOK and PE/CA-PJ15 lines were investigated by measuring apoptotic index using Hoechst stain. Results: In DOK and PE/CA-PJ15 cell lines, cytotoxicity was significant at extract concentrations of 11.25, 13.50 and 15.75 mg/mL, while extract concentration of 13.50 mg/mL produced significant cytotoxic effects on PDL cell line (p < 0.05). The percentage of apoptotic cells significantly increased at extract concentration of 11.25 mg/mL for both DOK and PE/CA-PJ15 cell lines (p < 0.05). Conclusion: Significant cytotoxic effects of aqueous root extract of S. persica appeared at a lower concentration in oral epithelial dysplasia and oral cancer cell lines than in normal PDL cell line. These results suggest the potential of S. persica for preventing oral cancer

A robust adaptive wavelet-based method for classification of meningioma histology images

Intra-class variability in the texture of samples is an important problem in the domain of histological image classification. This issue is inherent to the field due to the high complexity of histology image data. A technique that provides good results in one trial may fail in another when the test and training data are changed and therefore, the technique needs to be adapted for intra-class texture variation. In this paper, we present a novel wavelet based multiresolution analysis approach to meningioma subtype classification in response to the challenge of data variation.We analyze the stability of Adaptive Discriminant Wavelet Packet Transform (ADWPT) and present a solution to the issue of variation in the ADWPT decomposition when texture in data changes. A feature selection approach is proposed that provides high classification accuracy